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Description

Biomedical imaging researchers manage large quantities of heterogeneous data, often using spreadsheets. However, limitations of spreadsheet-based systems may cause workflow challenges. We examined the data management processes of a research center at an academic hospital which manages clinical and MRI research data using spreadsheets. Through surveys, interviews, and focus groups, we characterized their workflow and needs and proposed a new centralized data management model, which includes machine learning applications for greater efficiency and research reproducibility.

Learning Objective 1: Understand current challenges in data management for a biomedical imaging research group and be able to describe possible solutions in terms of data management practices, systems, and tools.

Authors:

Adriana Johnson (Presenter)
University of Pittsburgh

Jenna Schabdach, University of Pittsburgh
Lauren Rost, University of Pittsburgh
Harry Hochheiser, University of Pittsburgh

Presentation Materials:

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